A cost overrun, also known as a cost increase, underrated or budget overrun, involves unexpected costs incurred in excess of budgeted amounts due to an underestimation of the actual cost during budgeting. Cost overrun should be distinguished from cost escalation, which is used to express an anticipated growth in a budgeted cost due to factors such as inflation.
Cost overrun is common in infrastructure, building, and technology projects. For IT projects, a 2004 industry study by the Standish Group found an average cost overrun of 43 percent; 71 percent of projects came in over budget, exceeded time estimates, and had estimated too narrow a scope; and total waste was estimated at $55 billion per year in the US alone.
Many major construction projects have incurred cost overruns; cost estimates used to decide whether important transportation infrastructure should be built can mislead grossly and systematically.
Recent works by Ahiaga-Dagbui and Smith suggests a rethink of what is traditionally referred to as overruns in construction. They attempt to make a distinction between the often conflated causes of construction cost underestimation and eventual cost overruns. Critical to their argument is the point of reference for measuring cost overruns. Whereas some measure the size of cost overruns as the difference between cost at the time of decision to build and final completion costs, others measure the size of overruns as the difference between cost at contract award and final completion cost.This leads to a wide range in the size of overruns reported in different studies.
Three types of explanation for cost overrun exist: technical, psychological, and political-economic. Technical explanations account for cost overrun in terms of imperfect forecasting techniques, inadequate data, etc. Psychological explanations account for overrun in terms of optimism bias with forecasters. Scope creep, where the requirements or targets rises during the project, is common. Finally, political-economic explanations see overrun as the result of strategic misrepresentation of scope or budgets. Historically, political explanations for cost overrun have been seen to be the most dominant. In the USA, the architectural firm Home Architects has attributed this to a human trait they call "Psychology of Construction Cost Denial", regarding the cost inflation of custom homes.
A less explored possible cause of cost overruns on construction project is the escalation of commitment to a course of action. This theory, grounded in social psychology and organisation behaviour, suggests the tendency of people and organisations to become locked-in and entrapped in a particular course of action and thereby 'throw good money after bad' to make the venture succeed. This defies conventional rationality behind subjective expected utility theory. Ahiaga-Dagbui and Smith explore the effects of escalation of commitment on project delivery in construction using the case of the Scottish Parliament project. Also, a recent study has suggested that principles of chaos theory can be employed to understand how cost overruns emerge in megaprojects. This paper seeks to reclassify megaprojects as chaotic systems that are nonlinear and therefore difficult to predict. Using cases of cost overruns in oil and gas megaprojects, this study makes strong argument that chaos theory can indeed be a silver bullet in finding solutions to the recurring problem of cost overruns in megaprojects.
Prevention and mitigation
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In IT projects (essentially meaning software development projects in this context), the traditional approach to try to control costs is the use of project management techniques, such as PRINCE2 - though the use of such techniques has not prevented cost overruns in all cases. In the 21st century, a newer family of approaches, collectively termed agile software development, have grown in popularity for IT projects - although conventional project management is still very widely used, and in some cases has merely been inaccurately "rebranded" as agile.
Agile development does not claim to guarantee perfect on-time and on-budget delivery of the original expectations (which may not be even realistic or suitable to meet user needs). However, in many cases it may be able to:
- converge faster on a suitable solution
- meet user needs faster (users may even be able to use a partially implemented system and therefore obtain economic benefit from it during the project's implementation, depending on the nature of the project)
- catch bugs faster, maybe even when they only exist in the primordial form of requirements deficiencies, and hence be able to fix them more cheaply on average (because studies have shown bugs are more expensive to fix the later they are found)
- trim away unnecessary or even unwanted "nice to haves" from the list of features planned to be implemented, in order to cut costs (in this setting, the traditional software engineering term "requirements" is clearly seen to be something of a misnomer, as many so-called requirements aren't actually requirements at all)
- avoid the worst-case scenario: project cancellation, in which all the money is wasted (except possibly that portion of the money spent on reusable code and/or reusable software components, if they are considered to be worth reusing)
It has been claimed that agile development did not prevent cost and time overruns in the UK government's Universal Credit IT project, but there are serious doubts as to whether the Universal Credit software development project was in fact following a proper agile process in the first place.
In response to problem of cost overruns on major projects, the UK Government set up a Major Projects Authority to provide project assurance to HM Treasury and other Government departments undertaking major projects. Independent review of the financial effectiveness of project assurance in reducing cost overruns found the project assurance process to be effective in reducing cost overruns and recommended an expansion of the process to cover most of the Government's project portfolio. Project assurance is now also being used by private sector companies undertaking major projects.
Eriksson and Westerberg (2011); Li, Arditi, and Wang (2012); Chen and Manley (2014), and Cardenas, Voordijk, and Dewulf (2017) have hypothesized, developed and extensively tested conceptual models in which relevant project governance instruments and factors were identified and related to the performance and the reduction in costs overruns of projects.
Cost overrun can be described in multiple ways.
- As a percentage of the total expenditure
- As a total percentage including and above the original budget
- As a percentage of the cost overruns to original budget
For example, consider a bridge with a construction budget of $100 million where the actual cost was $150 million. This scenario could be truthfully represented by the following statement
- The cost overruns constituted 33% of the total expense.
- The budget for the bridge increased to 150%.
- The cost overruns exceeded the original budget by 50%.
The final example is the most commonly used as it specifically describes the cost overruns exclusively whereas the other two describe the overrun as an aspect of the total expense. In any case care should be taken to accurately describe what is meant by the chosen percentage so as to avoid ambiguity.
List of projects with large cost overruns
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- Sydney Opera House was completed ten years late and more than fourteen times over budget.
- National Programme for IT, described by the British Members of Parliament (in the Public Accounts Committee) as one of the "worst and most expensive contracting fiascos" in the history of government contracts
- Scottish Parliament Building
- Edinburgh Trams
- The Boeing Dreamliner programme, announced in 2003, was supposed to cost $6 billion and see the plane take to the air in 2008. The final bill was closer to $32 billion; and the 787 arrived three years late.
- Berlin Brandenburg Airport: 1 billion Euro => 6 billion Euro = 600%
- Elbe Philharmonic Hall in Hamburg : 77 million Euro => 789 million Euro = 1024%
- Landesarchiv Nordrhein-Westfalen in Duisburg : 30 million Euro => 195 million Euro = 650%
- Staatsoper Unter den Linden: 240 million Euro => >400 million Euro = >166 %
- Admissible heuristic
- Benefit shortfall
- Escalation of commitment
- Optimism bias
- Planning fallacy
- Reference class forecasting
- Scope creep
- Standish Group (2004). CHAOS Report (Report). West Yarmouth, Massachusetts: Standish Group.
- Flyvbjerg, Bent; Holm, Mette K. Skamris; Buhl, Søren L. (2002). "Underestimating Costs in Public Works Projects: Error or Lie?". Journal of the American Planning Association. 68 (3): 279–295. arXiv: . SSRN .
- Ahiaga-Dagbui, Dominic D.; Smith, Simon D. (2014). "Dealing with construction cost overruns using data mining". Construction Management and Economics. 32 (7–8): 682. doi:10.1080/01446193.2014.933854.
- Cantarelli, Chantal C.; Flybjerg, Bent; Molin, Eric J. E.; van Wee, Bert (2010). "Cost Overruns in Large-Scale Transportation Infrastructure Projects: Explanations and Their Theoretical Embeddedness". European Journal of Transport and Infrastructure Research. 10 (1): 5–18. arXiv: . SSRN .
- Ahiaga-Dagbui, Dominic; Smith, Simon (2014). "Exploring escalation of commitment in construction project management: Case study of the Scottish parliament project". Proceedings 30th Annual ARCOM Conference. Association of Researchers in Construction Management: 753–762. ISBN 9780955239083.
- Stecklein, Jonette M.; Dabney, Jim; Dick, Brandon; Haskins, Bill; Lovell, Randy; Moroney, Gregory (2004). Error Cost Escalation Through the Project Life Cycle (Report). JSC-CN-8435.
- Eriksson, Erik C.; Westerberg, Mats (2011). "Effects of cooperative procurement procedures on construction project performance: A conceptual framework". International Journal of Project Management. 29 (2): 197–208. doi:10.1016/j.ijproman.2010.01.003.
- Li, Huimin C.; Arditi, David; Wang, Zhuofu (2013). "Factors That Affect Transaction Costs in Construction Projects". Journal of Construction Engineering and Management. 139 (1): 60–68. doi:10.1061/(ASCE)CO.1943-7862.0000573.
- Chen, Le; Karen, Manley (2014). "Validation of an instrument to measure governance and performance on collaborative infrastructure projects". Journal of Construction Engineering and Management. 140 (5). doi:10.1061/(ASCE)CO.1943-7862.0000834.
- Cardenas, IC; Voordijk, H; Dewulf, G (2017). "Beyond theory: Towards a probabilistic causation model to support project governance in infrastructure projects". International Journal of Project Management. doi:10.1016/j.ijproman.2017.01.002.
- The RISKS digest (focuses on failed and overran IT projects)